摘要
化工过程中的故障检测与诊断多通过对历史数据和知识的分析来进行。提出了一种新的故障检测与分析方法,利用动态模拟来监测化工过程,并在过程发生异常时及时进行故障诊断。这种方法所针对的是可由动态模型内部参数来表征的一类故障,这些参数可通过动态模型的在线校正获得。该方法不需要设计观测器来估算过程的不可测变量,还可以将故障检测和诊断任务同时进行。该方法被应用于了重力水箱系统和庚烷芳构化反应器系统,并同传统的参数估计方法进行了比较。
A novel fault detection and diagnosis method was proposed, using dynamic simulation to monitor chemical process and identify faults when large tracking deviations occur. It aims at parameter failures, in which the parameters are updated via on-line correction. As it can predict the trend of process and determine the existence of malfunctions meanwhile, this method does not need to design problem-specific observer to estimate unmeasured state variables, and can identify and diagnosis faults simultaneously as well. Linear least square was adopted as model correction algorithm according to the characteristics of the chemical process faults, computation speed could therefore be increased. Examples of the application of the proposed method are presented for the gravity water tank and the aromatization reactor, and the results are compared with those from the traditional methods.
出处
《系统仿真学报》
EI
CAS
CSCD
北大核心
2007年第12期2831-2835,共5页
Journal of System Simulation
基金
教育部留学回国人员科研启动基金(2005-29)
山东省优秀中青年科学家科研奖励基金(2006BS05005)
关键词
故障诊断
化工过程
动态模拟
参数估计
fault diagnosis
chemical process
dynamic simulation
parameter estimation
